In this paper we study a scheduling problem arising from executing numerical simulations on HPC architectures. With a constant number of parallel machines, the objective is to minimize the makespan under memory constraints for the machines. Those constraints come from a neighborhood graph G for the jobs. Motivated by a previous result on graphs G with bounded path-width, our focus is on the case when the neighborhood graph G has bounded tree-width. Our result is a bi-criteria fully polynomial time approximation algorithm based on a dynamic programming algorithm. It allows to find a solution within a factor of 1 + epsilon of the optimal makespan, where the memory capacity of the machines may be exceeded by a factor at most 1 + epsilon. This result relies on the use of a nice tree decomposition of G and its traversal in a specific way which may be useful on its own. The case of unrelated machines is also tractable with minor modifications.
翻译:在本文中,我们研究了在 HPC 结构上进行数字模拟所产生的时间安排问题。 使用数量不变的平行机器, 目标是在机器记忆力限制下最大限度地减少制造间隔。 这些限制来自对工作的邻里图G。 受G 图中带有捆绑路径宽度的先前结果的驱动, 我们的焦点是当邻里图G 将树宽捆绑在一起时的情况。 我们的结果是一种基于动态编程算法的双标准全多元时间近似算法。 它允许在最优型机器的1+ epsilon 的因子中找到一个解决方案, 其中机器的记忆能力最多可以被1 + epsilon 的因子超过。 这个结果依赖于使用G 和它的轨迹的优树分解, 其特定方式可能有用。 与此无关的机器的例子也可以在小的修改中进行牵引。